How generative AI is reinventing the world of retail

By Amber Hickman  |  Technology Record

Microsoft’s Shanthi Rajagopalan shares how generative artificial intelligence is driving innovation in the industry and improving supply chain operations, customer experience and predictive analysis

The key to success for any retail organisation lies in understanding its customers, product, supply chain operations and changing market trends and demands. To do this, they need access to data insights. However, getting this information has historically been a time-consuming and expensive process, according to Shanthi Rajagopalan, Microsoft’s head of solutions strategy, worldwide retail and consumer goods.

“In the past, getting insights out of your data required you to have access to and gather unstructured data, clean and organise it, then have a highly trained professional execute and interpret statistical analysis and pass this on to be further interpreted by the user of the insights,” says Rajagopalan. “This process requires specialised resources, and it also leaves businesses constrained by the quality of the data as well as their talent and the tools they possess.

“We see a lot of retail and consumer goods organisations that just ‘make do’ with the insights they have, which typically consist of simple regression, retrospective analysis and limited data exploration. In short, static reporting which serves up static insights.”

This type of data analysis is no longer sufficient for retail organisations contending with fluctuating market changes, supply chain disruption and customers seeking more streamlined shopping experiences. To stay ahead of the game, retailers need to be able to predict the future with more accuracy than before.

Generating innovation

Innovations such as generative and predictive AI are leading a technology revolution in the retail and consumer goods industry, enabling organisations to introduce solutions that deliver smarter and easier ways for customers to shop and for employees to operate the business. Generative AI also enables retailers to better understand their data and get meaningful insights into their business operations.

“Generative AI provides the ability to unlock insights from new sources, or unstructured data that has long been dark for the organisation, and access them using just natural language,” says Rajagopalan.

“Imagine the wealth of customer insights hidden in customer service call transcripts, for instance. You can find out what customers like and dislike about products, why they break, what else they would like to see – all these are forward-looking, open-ended insights.”

Domino’s Pizza is one of the retailers using AI to better understand its customers in the UK and Ireland. The organisation uses the Demand Planning feature in Microsoft Dynamics 365 Finance and Operations, which leverages AI to predict customer ordering trends without the need for hundreds of spreadsheets and with a forecast accuracy of 97.5 per cent. This means that Domino’s Pizza can better plan its supply chains, leading to less waste and a reduced carbon footprint.

Retailers can also use AI to create new experiences for customers and enhance the shopping journey.

“People want to find, not just search,” says Rajagopalan. “Businesses should be implementing improved search functions and rethinking interactions, personalisation, product catalogue tagging and matchmaking.

“If a shopper visits an online store and asks a question like ‘what shall I wear to my cousin’s wedding this spring?’, they receive personalised recommendations, while the business gets a deeper understanding of the customer’s needs and preferences.”

Carrefour, a French retail corporation that operates a chain of grocery and convenience stores, is one of the organisations taking this approach to adopting AI. The firm used Microsoft’s OpenAI Azure service to develop Hopla, a chatbot integrated into the Carrefour website that allows customers to ask for help with choosing products based on their budget, dietary restrictions and meal plan ideas.

This introduces an element of conversation into the shopping experience that will work to not only retain customers, but also attract new ones too.

“We often see marketing as a ‘one-way’ communication between a brand and consumers, with the brand shouting out into the world and hoping their message sticks,” says Rajagopalan. “Generative AI now enables brands and shoppers to have conversations in natural language and create personalised content. For instance, a brand can now generate three different versions of the same marketing campaign but tweak the language used in each one to better address the needs of different audience demographics.”

Easing the adoption process

Despite the growing number of use cases, there are many retail organisations that are still wary of adopting generative AI due to concerns regarding security, potential job redundancies, and more. However, there are steps they can take to mitigate the risks.

“With any new technology, every organisation should be fully vetting it and ensuring they have the right talent and processes to support it,” says Rajagopalan. “The process is no different with generative AI. But if you consider how broad its capabilities are and the fact that most people have already started using it in their personal lives, it is all the more important for organisations to define and publish responsible use policies and guidelines for their employees.”

Incorporating AI into business operations doesn’t have to be a complicated process, says Rajagopalan, noting that there are a range of solutions and resources that can help.

“An increasing number of software-as-a-service applications are shipping with generative AI features built-in,” she says. “This is a great way for businesses to see the benefits of generative AI and learn how to use and optimise it without having to take on the burden of building, governing and maintaining their own software.”

The Microsoft partner ecosystem is also working in this space to bring AI-powered solutions to retail organisations. At NRF 2024, which will take place on 14-16 January 2024 in New York, USA, firms including Blue Yonder, Fractal, Fashable and Sitecore will be at the Microsoft booth highlighting uses cases for the generative AI solutions they have built.

Taking the leap

The impact of AI on businesses is expected to continue growing in the future. According to a market research report published by Fortune Business Insights in June 2023, the market value of AI in retail is expected to grow by 34.1 per cent by 2030, reaching $55.5 billion.

For organisations that are taking a ‘wait and see approach’ to generative AI, the time to act may come sooner than later as, according to Rajagopalan, “soon, everyone will be using generative AI in their personal lives, and it will be harder to avoid employees and customers demanding it in work and personal life.”

Partner perspectives

We asked a selection of Microsoft partners how they are using Microsoft technology and AI to help retail and consumer goods clients improve supply chain management, in-store operations and customer engagement.

“Avalara Dynamics 365 integrations allow retailers to optimise supply chain efficiency, streamline in-store operations and elevate customer engagement,” said George Trantas, senior director of global marketplaces at Avalara. “The seamless data synchronisation enables informed decision-making by automating compliance and tax processes to mitigate risks, which allows businesses to focus on core operations.”

“First movers among enterprises are leveraging generative AI to automate repetitive tasks, offer superior customer service backed by generative AI and produce high-quality content that resonates with their target audience,” said Ramana Raju Nidadavolu, manager of go-to-market for Microsoft Practice at Infosys.

Powerful new AI-driven analytics tools that are easy to implement will drive productivity and efficiencies using Microsoft Teams,” said Hilary Oliver, chief marketing and experience officer at Tollring. “For instance, Tollring is soon launching AI-driven analytics of Teams call recordings to automate the detection of keywords and subject topics, helping people to find and analyse the conversations that matter.”